build: upgrade scikit-learn>=1.9.0 and scipy>=1.18.1 specifiers

[priya-sundaram-dev]

As requested in #15105 (cclauss), splitting the dependency-specifier upgrades out onto master.

Describe your change:

• scikit-learn: >=1.5.2 → >=1.9.0 (latest on PyPI)
• scipy: >=1.16.2 → >=1.18.1 (latest on PyPI)

uv.lock already resolved both to these versions, so only the recorded pyproject.toml specifiers changed — the locked resolution is unchanged. This is independent of the 3.15t RC experiment in #15105.

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
• Documentation change? (build/dependency configuration only — no algorithm files touched)

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[algorithms-keeper]

Closing this pull request as invalid

@priya-sundaram-dev, this pull request is being closed as the files submitted contains an invalid extension. This repository only accepts Python algorithms. Please read the Contributing guidelines first.

Invalid files in this pull request: uv.lock